Snow cover plays an essential role in climate change and
the hydrological cycle of the Tibetan Plateau. The widely used Moderate
Resolution Imaging Spectroradiometer (MODIS) snow products have two major
issues: massive data gaps due to frequent clouds and relatively low estimate
accuracy of snow cover due to complex terrain in this region. Here we
generate long-term daily gap-free snow cover products over the Tibetan
Plateau at 500 m resolution by applying a hidden Markov random field (HMRF)
technique to the original MODIS snow products over the past two decades. The
data gaps of the original MODIS snow products were fully filled by optimally
integrating spectral, spatiotemporal, and environmental information within
HMRF framework. The snow cover estimate accuracy was greatly increased by
incorporating the spatiotemporal variations of solar radiation due to
surface topography and sun elevation angle as the environmental contextual
information in HMRF-based snow cover estimation. We evaluated our snow
products, and the accuracy is 98.29 % in comparison with in situ observations, and
91.36 % in comparison with high-resolution snow maps derived from Landsat
images. Our evaluation also suggests that the incorporation of
spatiotemporal solar radiation as the environmental contextual information
in HMRF modeling, instead of the simple use of surface elevation as the
environmental contextual information, results in the accuracy of the snow
products increases by 2.71 % and the omission error decreases by 3.59 %.
The accuracy of our snow products is especially improved during snow
transitional period, and over complex terrains with high elevation and
sunny slopes. The new products can provide long-term and spatiotemporally
continuous information of snow cover distribution, which is critical for
understanding the processes of snow accumulation and melting, analyzing its
impact on climate change, and facilitating water resource management in
Tibetan Plateau. This dataset can be freely accessed from the National
Tibetan Plateau Data Center at https://doi.org/10.11888/Cryos.tpdc.272204
(Huang and Xu, 2022)....

HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model

10.5194/essd-14-4445-2022